This series of files compile analyses done for the global analysis of Chapter 1 (version of May 15th).

All analyses have been done with PRIMER-e 6 and R 3.6.3.

Click on the table of contents in the left margin to assess a specific analysis.
Click on a figure to zoom it

We used data from subtidal ecosystems (see metadata files for more information). Only stations that have been sampled both for abiotic parameters and benthic species were included.

Selected variables for the analyses:

1. Data manipulation

For the following analyses, independant variables are habitat parameters and heavy metal concentrations, dependant variables are diversity indices. Variables have been standardized by mean and standard-deviation.

1.1. Identification of outliers

To identify stations that are not consistent with the others, we used the multivariate Cook’s Distance (CD) on the uncorrelated variables. A significative threshold of 4 times the mean of CD has been established.

0.5 mm community

We identified the following stations as general outliers:

  • stations 30, 127, 138, 144, 183, 228, 237 for habitat
  • stations 1, 11, 22, 25, 35, 127, 132, 139, 231 for metals

They have been deleted for the following analyses.

1 mm community

We identified the following stations as general outliers:

  • stations 72, 82, 107, 129, 144, 202, 249 for habitat
  • stations 106, 108, 110, 120, 127, 130, 139, 154, 232 for metals

They have been deleted for the following analyses.

1.2. Correlations between parameters

Correlations have been calculated with Spearman’s rank coefficient.

0.5 mm community

According to these results, the following variables are highly correlated (\(|\rho|\) > 0.80) so they have been considered together in the regressions:

  • chromium, iron and manganese (iron and manganese deleted)
  • copper, lead and zinc (copper and lead deleted)

We decided to exclude silt content, as it tends to drasticaly increase VIFs due to a marginal correlation with organic matter (\(R^{2}_{adj}\) = 0.21).

Correlation coefficients between habitat parameters (0.5 mm community subset)
  depth om gravel sand silt clay delta delta_plus delta_star
depth 1 0.298 -0.26 0.209 0.497 -0.483 0.468 0.361 0.211
om 0.298 1 -0.504 -0.407 0.479 0.01 -0.074 -0.237 -0.368
gravel -0.26 -0.504 1 0.019 -0.347 0.162 0.076 0.001 0.147
sand 0.209 -0.407 0.019 1 -0.007 -0.749 0.128 0.35 0.348
silt 0.497 0.479 -0.347 -0.007 1 -0.534 0.214 0.284 0.087
clay -0.483 0.01 0.162 -0.749 -0.534 1 -0.263 -0.432 -0.363
delta 0.468 -0.074 0.076 0.128 0.214 -0.263 1 0.252 0.27
delta_plus 0.361 -0.237 0.001 0.35 0.284 -0.432 0.252 1 0.618
delta_star 0.211 -0.368 0.147 0.348 0.087 -0.363 0.27 0.618 1
Correlation coefficients between metals (0.5 mm community subset)
  arsenic cadmium chromium copper iron manganese mercury lead zinc delta delta_plus delta_star
arsenic 1 0.732 0.631 0.713 0.405 0.62 0.711 0.865 0.808 -0.137 -0.147 -0.329
cadmium 0.732 1 0.784 0.691 0.514 0.669 0.66 0.854 0.838 -0.245 -0.084 -0.322
chromium 0.631 0.784 1 0.738 0.8 0.891 0.467 0.75 0.792 -0.333 -0.27 -0.361
copper 0.713 0.691 0.738 1 0.571 0.738 0.612 0.843 0.928 -0.283 -0.286 -0.529
iron 0.405 0.514 0.8 0.571 1 0.83 0.187 0.458 0.571 -0.269 -0.142 -0.266
manganese 0.62 0.669 0.891 0.738 0.83 1 0.463 0.681 0.738 -0.321 -0.302 -0.434
mercury 0.711 0.66 0.467 0.612 0.187 0.463 1 0.787 0.683 -0.085 0.027 -0.25
lead 0.865 0.854 0.75 0.843 0.458 0.681 0.787 1 0.928 -0.251 -0.181 -0.426
zinc 0.808 0.838 0.792 0.928 0.571 0.738 0.683 0.928 1 -0.271 -0.195 -0.458
delta -0.137 -0.245 -0.333 -0.283 -0.269 -0.321 -0.085 -0.251 -0.271 1 0.312 0.352
delta_plus -0.147 -0.084 -0.27 -0.286 -0.142 -0.302 0.027 -0.181 -0.195 0.312 1 0.575
delta_star -0.329 -0.322 -0.361 -0.529 -0.266 -0.434 -0.25 -0.426 -0.458 0.352 0.575 1

1 mm community

According to these results, the following variables are highly correlated (\(|\rho|\) > 0.80) so they have been considered together in the regressions:

  • om and silt (silt deleted)
  • chromium, iron and manganese (iron and manganese deleted)
  • copper, lead and zinc (copper and lead deleted)
Correlation coefficients between habitat parameters (1 mm community subset)
  depth om gravel sand silt clay delta delta_plus delta_star
depth 1 0.442 -0.026 -0.328 0.317 -0.097 0.497 0.113 0.138
om 0.442 1 -0.304 -0.798 0.841 -0.125 0.273 -0.116 -0.163
gravel -0.026 -0.304 1 0.124 -0.383 -0.023 -0.099 0.027 -0.001
sand -0.328 -0.798 0.124 1 -0.927 -0.12 -0.19 0.143 0.169
silt 0.317 0.841 -0.383 -0.927 1 0.069 0.216 -0.133 -0.155
clay -0.097 -0.125 -0.023 -0.12 0.069 1 -0.112 -0.102 -0.113
delta 0.497 0.273 -0.099 -0.19 0.216 -0.112 1 0.166 0.17
delta_plus 0.113 -0.116 0.027 0.143 -0.133 -0.102 0.166 1 0.788
delta_star 0.138 -0.163 -0.001 0.169 -0.155 -0.113 0.17 0.788 1
Correlation coefficients between metals (1 mm community subset)
  arsenic cadmium chromium copper iron manganese mercury lead zinc delta delta_plus delta_star
arsenic 1 0.743 0.79 0.809 0.636 0.707 0.702 0.892 0.88 -0.053 0.016 -0.123
cadmium 0.743 1 0.772 0.639 0.541 0.662 0.669 0.833 0.812 -0.257 -0.109 -0.291
chromium 0.79 0.772 1 0.858 0.823 0.902 0.667 0.837 0.892 -0.156 -0.009 -0.224
copper 0.809 0.639 0.858 1 0.77 0.792 0.708 0.857 0.946 -0.092 0.014 -0.164
iron 0.636 0.541 0.823 0.77 1 0.869 0.412 0.595 0.753 -0.099 0.097 -0.086
manganese 0.707 0.662 0.902 0.792 0.869 1 0.573 0.705 0.79 -0.148 0.023 -0.199
mercury 0.702 0.669 0.667 0.708 0.412 0.573 1 0.844 0.743 -0.138 -0.12 -0.275
lead 0.892 0.833 0.837 0.857 0.595 0.705 0.844 1 0.928 -0.128 -0.102 -0.275
zinc 0.88 0.812 0.892 0.946 0.753 0.79 0.743 0.928 1 -0.137 -0.004 -0.194
delta -0.053 -0.257 -0.156 -0.092 -0.099 -0.148 -0.138 -0.128 -0.137 1 0.231 0.318
delta_plus 0.016 -0.109 -0.009 0.014 0.097 0.023 -0.12 -0.102 -0.004 0.231 1 0.703
delta_star -0.123 -0.291 -0.224 -0.164 -0.086 -0.199 -0.275 -0.275 -0.194 0.318 0.703 1

2. Cluster characteristics

This section present each clusters, with (i) the average values for habitat and metal variables, (ii) the average values for diversity indices and (iii) the characteristic taxa obtained by SIMPER and IndVal analyses.

0.5 mm community
Habitat and metals
Cluster 1
  Mean SD SE Median Min Max 95% CI
depth 6.994 1.403 0.351 7.100 4.500 8.900 0.687
om 2.584 1.660 0.415 2.378 1.108 8.260 0.813
gravel 0.000 0.000 0.000 0.000 0.000 0.000 0.000
sand 0.000 0.000 0.000 0.000 0.000 0.000 0.000
silt 0.001 0.000 0.000 0.001 0.001 0.001 0.000
clay 0.999 0.000 0.000 0.999 0.999 0.999 0.000
arsenic 3.744 1.293 0.323 3.750 1.50 6.00 0.633
cadmium 0.146 0.027 0.007 0.140 0.09 0.19 0.013
chromium 80.287 22.934 5.734 79.450 45.80 143.30 11.238
copper 19.887 5.319 1.330 19.600 11.20 32.40 2.606
iron 64730.012 14916.663 3729.166 64356.210 32899.91 98544.60 7309.030
manganese 2173.444 1284.808 321.202 2048.495 705.69 5962.19 629.544
mercury 0.036 0.063 0.016 0.020 0.00 0.25 0.031
lead 7.316 2.312 0.578 7.115 3.59 12.18 1.133
zinc 77.213 16.879 4.220 74.900 47.10 101.50 8.270
Cluster 2
  Mean SD SE Median Min Max 95% CI
depth 13.720 12.804 1.639 8.800 1.600 60.600 3.213
om 0.524 0.337 0.043 0.409 0.186 1.528 0.084
gravel 0.059 0.142 0.018 0.000 0.000 0.701 0.036
sand 0.533 0.415 0.053 0.675 0.000 1.000 0.104
silt 0.113 0.187 0.024 0.032 0.000 0.869 0.047
clay 0.295 0.441 0.056 0.000 0.000 1.000 0.111
arsenic 2.506 1.282 0.187 2.2 1.10 7.600 0.367
cadmium 0.110 0.041 0.006 0.1 0.03 0.220 0.012
chromium 54.502 25.249 3.683 47.4 10.90 125.000 7.218
copper 6.857 5.021 0.732 5.0 2.20 22.100 1.435
iron 57555.237 30299.094 4419.577 49344.4 14089.92 188857.220 8662.212
manganese 930.994 424.869 61.974 833.6 251.67 2298.700 121.466
mercury 0.007 0.010 0.001 0.0 0.00 0.036 0.003
lead 3.259 1.813 0.265 2.6 1.02 9.500 0.518
zinc 43.540 15.429 2.251 41.7 15.90 101.400 4.411
Cluster 3
  Mean SD SE Median Min Max 95% CI
depth 32.756 19.095 2.024 29.500 2.100 77.000 3.967
om 1.762 0.965 0.102 1.525 0.392 4.415 0.201
gravel 0.017 0.097 0.010 0.000 0.000 0.765 0.020
sand 0.463 0.220 0.023 0.512 0.000 0.868 0.046
silt 0.491 0.209 0.022 0.480 0.021 0.845 0.043
clay 0.030 0.148 0.016 0.000 0.000 0.979 0.031
arsenic 3.886 2.276 0.243 3.050 1.80 16.000 0.475
cadmium 0.137 0.031 0.003 0.140 0.06 0.230 0.007
chromium 58.073 16.012 1.707 58.600 31.10 110.700 3.345
copper 12.334 4.772 0.509 13.100 3.60 28.700 0.997
iron 55265.811 15722.531 1676.027 55752.250 28355.90 151226.400 3284.953
manganese 1180.457 582.751 62.122 1020.300 423.10 3435.200 121.756
mercury 0.024 0.016 0.002 0.021 0.00 0.087 0.003
lead 5.455 1.888 0.201 5.400 1.70 12.100 0.394
zinc 61.091 16.640 1.774 62.950 27.60 141.000 3.477
Diversity
Cluster 1
  Mean SD SE Median Min Max 95% CI
S 27.812 3.781 0.945 28.500 21.000 34.000 1.853
N 1411.188 410.971 102.743 1433.000 636.000 2103.000 201.372
H 1.823 0.268 0.067 1.882 1.246 2.247 0.131
J 0.550 0.081 0.020 0.559 0.409 0.682 0.040
delta 38.494 6.594 1.648 39.262 25.409 49.097 3.231
delta_plus 63.663 1.847 0.462 63.735 58.995 67.300 0.905
delta_star 51.896 4.667 1.167 52.793 44.058 59.625 2.287
Cluster 2
  Mean SD SE Median Min Max 95% CI
S 12.197 6.077 0.778 12.000 1 35.000 1.525
N 110.131 175.663 22.491 56.000 1 941.000 44.082
H 1.619 0.612 0.078 1.623 0 2.737 0.154
J 0.683 0.213 0.027 0.706 0 1.000 0.053
delta 50.139 16.129 2.065 53.777 0 77.778 4.048
delta_plus 68.787 9.821 1.257 70.351 0 77.778 2.465
delta_star 70.279 10.910 1.397 72.837 0 79.812 2.738
Cluster 3
  Mean SD SE Median Min Max 95% CI
S 13.270 4.871 0.516 13.000 4.000 24.000 1.012
N 92.180 71.364 7.565 75.000 4.000 450.000 14.826
H 1.896 0.430 0.046 1.971 0.975 2.577 0.089
J 0.758 0.129 0.014 0.781 0.402 1.000 0.027
delta 55.694 9.436 1.000 58.642 28.289 75.926 1.960
delta_plus 70.368 1.994 0.211 70.370 63.333 75.926 0.414
delta_star 71.045 3.169 0.336 71.358 59.142 79.779 0.658

Here are the graphs plotting specific richness and taxonomic distinctness:

As a measure of \(\beta\) diversity, mean Bray-Curtis dissimilarity is:

  • 0.38 within cluster 1
  • 0.85 within cluster 2
  • 0.69 within cluster 3
Characteristic taxa
##                             cluster indicator_value probability
## capitella_sp                      1          0.9861       0.001
## nephtys_sp                        1          0.9861       0.001
## prionospio_steenstrupi            1          0.9692       0.001
## phyllodoce_groenlandica           1          0.9664       0.001
## cirratulidae_spp                  1          0.9331       0.001
## phoronida                         1          0.9288       0.001
## scoloplos_armiger                 1          0.8889       0.001
## sarsicytheridea_sp                1          0.8706       0.001
## polychaeta                        1          0.8100       0.001
## limecola_balthica                 1          0.7949       0.001
## sertulariidae_spp                 1          0.7531       0.001
## eteone_sp                         1          0.7064       0.001
## bipalponephtys_neotena            1          0.6982       0.001
## campanulariidae_spp               1          0.6946       0.001
## harpacticoida                     1          0.5711       0.001
## euchone_analis                    1          0.5625       0.001
## pholoe_longa                      1          0.5096       0.001
## podocopida                        1          0.4323       0.001
## glycera_dibranchiata              1          0.4297       0.001
## hediste_diversicolor              1          0.4257       0.001
## tharyx_sp                         1          0.3750       0.001
## diastylis_sculpta                 1          0.3651       0.001
## phoxocephalus_holbolli            1          0.3346       0.009
## pholoe_minuta_tecta               1          0.3282       0.001
## praxillella_praetermissa          1          0.3099       0.001
## microphthalmus_sczelkowii         1          0.3009       0.001
## aricidea_sp                       1          0.2998       0.001
## sabellidae_spp                    1          0.2959       0.001
## solenoidea                        1          0.2878       0.001
## pholoe_sp                         1          0.2770       0.045
## microphthalmus_sp                 1          0.2500       0.001
## pontoporeia_femorata              1          0.2477       0.013
## axinopsida_orbiculata             1          0.2457       0.007
## eucratea_loricata                 1          0.2286       0.002
## bivalvia                          1          0.2090       0.004
## cylichna_alba                     1          0.1875       0.003
## harmothoe_imbricata               1          0.1875       0.002
## eudendriidae_spp                  1          0.1724       0.002
## gammaridea                        1          0.1680       0.007
## hemicythere_villosa               1          0.1624       0.004
## spio_filicornis                   1          0.1403       0.013
## eteone_longa                      1          0.1250       0.010
## hartmania_moorei                  1          0.1250       0.006
## macoma_sp                         1          0.1250       0.012
## monticellina_sp                   1          0.1250       0.010
## pherusa_sp                        1          0.1250       0.006
## scoletoma_tetraura                1          0.1250       0.012
## capitellidae_spp                  1          0.1193       0.009
## brachyura                         1          0.1183       0.007
## lumbrineridae_spp                 1          0.0902       0.043
## serripes_groenlandicus            1          0.0509       0.049
## echinarachnius_parma              2          0.5050       0.001
## nematoda                          2          0.3257       0.007
## spisula_solidissima               2          0.2951       0.001
## crenella_decussata                2          0.2317       0.004
## annelida                          2          0.2131       0.006
## polygordius_sp                    2          0.1894       0.009
## nephtys_caeca                     2          0.1754       0.034
## orchomenella_minuta               2          0.1003       0.038
## halacaridae_spp                   2          0.0984       0.050
## ophiura_robusta                   2          0.0984       0.049
## lepeta_caeca                      2          0.0912       0.031
## hiatella_arctica                  2          0.0899       0.046
## macoma_calcarea                   3          0.6715       0.001
## eudorellopsis_integra             3          0.6687       0.001
## ennucula_tenuis                   3          0.4903       0.001
## leucon_leucon_nasicoides          3          0.4655       0.001
## goniada_maculata                  3          0.4399       0.001
## protomedeia_grandimana            3          0.3599       0.001
## ostracoda                         3          0.3403       0.001
## nephtys_incisa                    3          0.3293       0.002
## thyasira_gouldi                   3          0.3186       0.001
## akanthophoreus_gracilis           3          0.3118       0.003
## amphipoda                         3          0.2632       0.015
## quasimelita_formosa               3          0.2374       0.007
## aceroides_aceroides_latipes       3          0.2267       0.012
## chaetodermatida                   3          0.1566       0.028
## sipuncula                         3          0.1410       0.050
## 
## Sum of probabilities                 =  81.144 
## 
## Sum of Indicator Values              =  35.53 
## 
## Sum of Significant Indicator Values  =  29.25 
## 
## Number of Significant Indicators     =  78 
## 
## Significant Indicator Distribution
## 
##  1  2  3 
## 51 12 15
Phylum abundances by cluster
phylum cl1 cl2 cl3
Annelida 20206 1497 3099
Phoronida 1137 3 0
Arthropoda 861 2199 3472
Mollusca 327 1404 1168
Cnidaria 36 50 0
Bryozoa 6 24 0
Echinodermata 4 538 37
Hemichordata 2 0 0
Chaetognatha 0 1 0
Nematoda 0 982 395
Nemertea 0 17 4
Sipuncula 0 3 29

SIMPER results between clusters 1 and 2 (mean between-group Bray-Curtis dissimilarity: 0.925)
  average sd ratio ava avb cumsum
bipalponephtys_neotena 0.0735 0.0147 4.99 6.17 0.278 0.0794
nephtys_sp 0.0726 0.0124 5.85 5.92 0.0682 0.158
prionospio_steenstrupi 0.0494 0.0129 3.84 4.09 0.13 0.211
phoronida 0.0439 0.0162 2.71 3.64 0.0341 0.259
scoloplos_armiger 0.0437 0.0189 2.32 3.7 0.202 0.306
capitella_sp 0.0392 0.0111 3.53 3.23 0.0455 0.348
phyllodoce_groenlandica 0.0382 0.0101 3.8 3.23 0.113 0.39
cirratulidae_spp 0.0298 0.0122 2.45 2.42 0.0114 0.422
sarsicytheridea_sp 0.027 0.0139 1.95 2.26 0.0114 0.451
limecola_balthica 0.0251 0.0154 1.63 2.05 0.0455 0.478
harpacticoida 0.0211 0.0129 1.63 2.21 0.902 0.501
eteone_sp 0.0192 0.0129 1.49 1.62 0.0768 0.522
phoxocephalus_holbolli 0.0169 0.0133 1.27 1.36 1.02 0.54
euchone_analis 0.0164 0.017 0.964 1.43 0 0.558
nematoda 0.0151 0.02 0.756 0 1.21 0.574
pholoe_sp 0.0149 0.0145 1.03 1.19 0.258 0.59
pholoe_longa 0.0145 0.0141 1.03 1.21 0.0965 0.606
echinarachnius_parma 0.0134 0.0139 0.966 0 1.1 0.62
pholoe_minuta_tecta 0.0123 0.0162 0.757 0.959 0.137 0.633
podocopida 0.0112 0.0154 0.727 0.944 0.0114 0.646
sabellidae_spp 0.0108 0.0152 0.708 0.909 0.0114 0.657
pontoporeia_femorata 0.0104 0.013 0.8 0.804 0.0114 0.668
hediste_diversicolor 0.0102 0.00999 1.02 0.842 0.102 0.679
microphthalmus_sczelkowii 0.0094 0.0143 0.657 0.761 0.0294 0.69
diastylis_sculpta 0.00927 0.0122 0.758 0.783 0.0114 0.7
SIMPER results between clusters 1 and 3 (mean between-group Bray-Curtis dissimilarity: 0.904)
  average sd ratio ava avb cumsum
nephtys_sp 0.07 0.0112 6.23 5.92 0.0156 0.0774
prionospio_steenstrupi 0.0487 0.0107 4.56 4.09 0 0.131
bipalponephtys_neotena 0.0457 0.0192 2.38 6.17 2.39 0.182
scoloplos_armiger 0.0438 0.0176 2.49 3.7 0 0.23
phoronida 0.0423 0.0155 2.73 3.64 0 0.277
capitella_sp 0.0379 0.0102 3.73 3.23 0 0.319
phyllodoce_groenlandica 0.0379 0.0086 4.4 3.23 0 0.361
cirratulidae_spp 0.0286 0.0116 2.47 2.42 0 0.393
sarsicytheridea_sp 0.026 0.0133 1.95 2.26 0 0.421
limecola_balthica 0.0244 0.0149 1.64 2.05 0 0.448
harpacticoida 0.0215 0.012 1.78 2.21 0.519 0.472
eudorellopsis_integra 0.0191 0.0161 1.18 0.0687 1.68 0.493
eteone_sp 0.0187 0.0124 1.5 1.62 0.0234 0.514
macoma_calcarea 0.0158 0.0112 1.41 0.0687 1.4 0.531
euchone_analis 0.0157 0.0163 0.964 1.43 0 0.549
phoxocephalus_holbolli 0.0153 0.0128 1.19 1.36 0.156 0.566
pholoe_sp 0.0143 0.0118 1.21 1.19 0.702 0.582
pholoe_longa 0.014 0.0138 1.01 1.21 0.0297 0.597
pontoporeia_femorata 0.0124 0.0129 0.965 0.804 0.605 0.611
sabellidae_spp 0.0114 0.0149 0.768 0.909 0.232 0.623
pholoe_minuta_tecta 0.0112 0.0156 0.716 0.959 0 0.636
podocopida 0.0107 0.0147 0.724 0.944 0 0.648
hediste_diversicolor 0.00966 0.00911 1.06 0.842 0.169 0.658
leucon_leucon_nasicoides 0.00947 0.0124 0.765 0 0.828 0.669
diastylis_sculpta 0.00943 0.0117 0.806 0.783 0.144 0.679
protomedeia_grandimana 0.0092 0.011 0.836 0 0.803 0.689
axinopsida_orbiculata 0.00915 0.011 0.831 0.677 0.322 0.7
SIMPER results between clusters 2 and 3 (mean between-group Bray-Curtis dissimilarity: 0.917)
  average sd ratio ava avb cumsum
bipalponephtys_neotena 0.065 0.0407 1.6 0.278 2.39 0.0709
eudorellopsis_integra 0.0484 0.0439 1.1 0.0294 1.68 0.124
nematoda 0.0427 0.0502 0.85 1.21 0.676 0.17
macoma_calcarea 0.0396 0.0335 1.18 0.289 1.4 0.213
echinarachnius_parma 0.0331 0.0368 0.901 1.1 0.15 0.25
phoxocephalus_holbolli 0.0289 0.034 0.85 1.02 0.156 0.281
harpacticoida 0.0277 0.0291 0.952 0.902 0.519 0.311
protomedeia_grandimana 0.0265 0.0344 0.768 0.225 0.803 0.34
leucon_leucon_nasicoides 0.0232 0.0308 0.753 0.0114 0.828 0.365
ennucula_tenuis 0.0216 0.0246 0.877 0.0774 0.774 0.389
pholoe_sp 0.0211 0.0228 0.926 0.258 0.702 0.412
spisula_solidissima 0.0209 0.0386 0.542 0.753 0 0.435
pontoporeia_femorata 0.0186 0.0339 0.549 0.0114 0.605 0.455
amphipoda 0.0156 0.021 0.741 0.185 0.452 0.472
goniada_maculata 0.0149 0.0202 0.736 0.0114 0.523 0.488
maldanidae_spp 0.0148 0.0282 0.523 0.0114 0.529 0.504
ostracoda 0.0138 0.0208 0.664 0.0455 0.507 0.52
thyasira_gouldi 0.0134 0.0224 0.599 0.0114 0.498 0.534
akanthophoreus_gracilis 0.0131 0.0212 0.619 0.0227 0.506 0.548
nephtys_incisa 0.0109 0.0164 0.668 0.0341 0.371 0.56
oligochaeta 0.0107 0.0258 0.415 0.166 0.266 0.572
polynoidae_spp 0.0106 0.0181 0.584 0.0638 0.341 0.584
axinopsida_orbiculata 0.0103 0.0222 0.462 0.0341 0.322 0.595
crenella_decussata 0.00963 0.02 0.482 0.328 0.0201 0.605
mytilus_sp 0.00954 0.0219 0.436 0.341 0.0824 0.616
thracia_septentrionalis 0.0094 0.0201 0.467 0.19 0.183 0.626
caprella_septentrionalis 0.00934 0.0273 0.342 0.33 0.0549 0.636
quasimelita_formosa 0.00927 0.0175 0.53 0.0294 0.332 0.646
polygordius_sp 0.00916 0.0207 0.443 0.359 0 0.656
cistenides_granulata 0.00881 0.0162 0.543 0.217 0.145 0.666
nephtys_caeca 0.00802 0.0146 0.55 0.226 0.0435 0.675
aceroides_aceroides_latipes 0.00741 0.0149 0.497 0.0114 0.279 0.683
hediste_diversicolor 0.0073 0.0182 0.401 0.102 0.169 0.691
ameritella_agilis 0.00717 0.0166 0.432 0.192 0.0591 0.698
1 mm community
Habitat and metals
Cluster 1
  Mean SD SE Median Min Max 95% CI
depth 21.047 17.145 1.860 18.500 1.0 66.600 3.645
om 0.707 0.694 0.075 0.463 0.2 3.872 0.148
gravel 0.068 0.151 0.016 0.000 0.0 0.809 0.032
sand 0.644 0.334 0.036 0.747 0.0 1.001 0.071
silt 0.245 0.272 0.030 0.094 0.0 0.942 0.058
clay 0.043 0.107 0.012 0.000 0.0 0.497 0.023
arsenic 3.635 3.562 0.543 2.600 1.10 21.30 1.065
cadmium 0.132 0.036 0.005 0.130 0.07 0.22 0.011
chromium 52.335 22.919 3.495 47.100 17.00 111.00 6.850
copper 9.516 6.891 1.051 8.200 2.40 28.80 2.060
iron 49567.672 15794.446 2408.630 45392.700 21938.10 86123.70 4720.829
manganese 890.974 434.031 66.189 777.700 318.40 2298.70 129.728
mercury 0.017 0.010 0.002 0.014 0.00 0.04 0.003
lead 4.712 2.619 0.399 3.900 2.00 12.10 0.783
zinc 54.735 26.325 4.015 47.500 26.90 141.40 7.868
Cluster 2
  Mean SD SE Median Min Max 95% CI
depth 11.800 10.108 2.918 8.350 3.300 34.300 5.719
om 0.365 0.200 0.058 0.308 0.186 0.895 0.113
gravel 0.010 0.036 0.010 0.000 0.000 0.124 0.020
sand 0.952 0.048 0.014 0.970 0.873 1.000 0.027
silt 0.035 0.041 0.012 0.022 0.000 0.116 0.023
clay 0.002 0.003 0.001 0.000 0.000 0.010 0.002
arsenic 1.550 1.061 0.750 1.550 0.80 2.300 1.470
cadmium 0.095 0.007 0.005 0.095 0.09 0.100 0.010
chromium 28.000 5.657 4.000 28.000 24.00 32.000 7.840
copper 6.850 3.182 2.250 6.850 4.60 9.100 4.410
iron 29010.700 991.222 700.900 29010.700 28309.80 29711.600 1373.739
manganese 494.950 102.743 72.650 494.950 422.30 567.600 142.391
mercury 0.014 0.005 0.004 0.014 0.01 0.017 0.007
lead 2.450 0.778 0.550 2.450 1.90 3.000 1.078
zinc 40.150 7.566 5.350 40.150 34.80 45.500 10.486
Cluster 3
  Mean SD SE Median Min Max 95% CI
depth 20.771 14.328 3.829 14.850 7.700 54.200 7.506
om 0.348 0.171 0.046 0.313 0.168 0.864 0.090
gravel 0.034 0.055 0.015 0.000 0.000 0.152 0.029
sand 0.895 0.116 0.031 0.958 0.614 1.000 0.061
silt 0.061 0.077 0.021 0.023 0.000 0.227 0.040
clay 0.009 0.016 0.004 0.005 0.000 0.061 0.008
arsenic 2.400 NA NA 2.400 2.400 2.400 NA
cadmium 0.100 NA NA 0.100 0.100 0.100 NA
chromium 42.200 NA NA 42.200 42.200 42.200 NA
copper 5.400 NA NA 5.400 5.400 5.400 NA
iron 42655.900 NA NA 42655.900 42655.900 42655.900 NA
manganese 719.400 NA NA 719.400 719.400 719.400 NA
mercury 0.007 NA NA 0.007 0.007 0.007 NA
lead 3.000 NA NA 3.000 3.000 3.000 NA
zinc 39.000 NA NA 39.000 39.000 39.000 NA
Cluster 4
  Mean SD SE Median Min Max 95% CI
depth 19.247 12.578 2.040 19.150 1.900 45.600 3.999
om 1.422 0.957 0.155 1.291 0.288 4.415 0.304
gravel 0.002 0.010 0.002 0.000 0.000 0.061 0.003
sand 0.544 0.255 0.041 0.548 0.027 0.979 0.081
silt 0.440 0.240 0.039 0.452 0.017 0.881 0.076
clay 0.014 0.045 0.007 0.000 0.000 0.257 0.014
arsenic 3.561 2.098 0.340 2.80 1.70 10.300 0.667
cadmium 0.144 0.045 0.007 0.14 0.06 0.270 0.014
chromium 56.361 17.276 2.802 53.70 31.10 106.000 5.493
copper 12.055 5.310 0.861 12.30 3.00 26.300 1.688
iron 56587.103 21180.977 3436.008 55570.40 28355.90 151226.400 6734.452
manganese 1144.161 619.999 100.577 980.70 423.10 3435.200 197.128
mercury 0.022 0.016 0.003 0.02 0.00 0.091 0.005
lead 5.326 2.064 0.335 5.40 1.70 12.200 0.656
zinc 60.976 18.310 2.970 59.75 27.60 130.000 5.822
Cluster 5
  Mean SD SE Median Min Max 95% CI
depth 42.408 17.402 2.437 35.800 18.500 77.000 4.776
om 2.028 0.898 0.126 1.818 0.353 3.707 0.247
gravel 0.028 0.129 0.018 0.000 0.000 0.765 0.035
sand 0.415 0.204 0.029 0.438 0.000 0.945 0.056
silt 0.517 0.226 0.032 0.487 0.020 0.845 0.062
clay 0.039 0.185 0.026 0.000 0.000 0.979 0.051
arsenic 4.255 2.554 0.358 4.000 1.900 16.000 0.701
cadmium 0.140 0.026 0.004 0.150 0.090 0.190 0.007
chromium 59.559 14.341 2.008 60.900 36.400 86.500 3.936
copper 12.404 4.307 0.603 13.300 4.500 21.400 1.182
iron 53753.192 10477.744 1467.178 54445.900 33130.000 74316.100 2875.615
manganese 1197.469 566.802 79.368 1056.100 494.400 2961.700 155.559
mercury 0.028 0.018 0.002 0.026 0.005 0.087 0.005
lead 5.786 1.687 0.236 6.100 2.700 9.300 0.463
zinc 62.076 13.955 1.954 66.400 35.600 93.900 3.830
Diversity
Cluster 1
  Mean SD SE Median Min Max 95% CI
S 6.482 3.810 0.413 6.000 1 17.000 0.810
N 38.706 83.830 9.093 17.000 1 674.000 17.821
H 1.295 0.564 0.061 1.330 0 2.555 0.120
J 0.761 0.228 0.025 0.821 0 1.000 0.048
delta 54.802 19.509 2.116 58.974 0 87.500 4.147
delta_plus 76.707 16.123 1.749 80.903 0 87.500 3.428
delta_star 76.380 16.689 1.810 81.020 0 87.500 3.548
Cluster 2
  Mean SD SE Median Min Max 95% CI
S 4.000 1.954 0.564 4.000 1 8.000 1.106
N 29.333 28.719 8.290 19.500 2 96.000 16.249
H 0.811 0.495 0.143 0.983 0 1.475 0.280
J 0.569 0.287 0.083 0.628 0 0.917 0.162
delta 38.465 23.723 6.848 45.487 0 72.024 13.422
delta_plus 75.945 24.326 7.022 81.920 0 87.500 13.763
delta_star 78.392 24.894 7.186 86.848 0 87.500 14.085
Cluster 3
  Mean SD SE Median Min Max 95% CI
S 2.214 0.893 0.239 2.000 1 4.000 0.468
N 9.643 8.381 2.240 7.500 2 33.000 4.390
H 0.553 0.390 0.104 0.606 0 1.213 0.204
J 0.611 0.381 0.102 0.701 0 1.000 0.200
delta 36.868 27.396 7.322 38.125 0 87.500 14.351
delta_plus 66.369 36.120 9.653 83.333 0 87.500 18.920
delta_star 66.351 36.138 9.658 84.133 0 87.500 18.930
Cluster 4
  Mean SD SE Median Min Max 95% CI
S 8.026 3.702 0.600 8.000 3.000 15.000 1.177
N 46.974 51.503 8.355 32.000 3.000 254.000 16.375
H 1.550 0.469 0.076 1.471 0.643 2.443 0.149
J 0.795 0.158 0.026 0.847 0.433 1.000 0.050
delta 58.766 13.647 2.214 59.778 20.356 79.167 4.339
delta_plus 79.302 3.156 0.512 79.634 71.250 85.000 1.003
delta_star 78.659 5.380 0.873 79.501 63.580 86.301 1.711
Cluster 5
  Mean SD SE Median Min Max 95% CI
S 11.667 3.333 0.467 11.000 5.000 19.000 0.915
N 47.863 24.492 3.430 42.000 8.000 131.000 6.722
H 1.959 0.374 0.052 1.968 0.839 2.646 0.103
J 0.809 0.115 0.016 0.837 0.469 0.980 0.031
delta 64.449 10.464 1.465 68.472 27.922 75.893 2.872
delta_plus 79.941 2.066 0.289 79.722 73.750 83.889 0.567
delta_star 79.036 3.948 0.553 79.453 68.617 88.001 1.084

Here are the graphs plotting specific richness and taxonomic distinctness:

As a measure of \(\beta\) diversity, mean Bray-Curtis dissimilarity is:

  • 0.93 within cluster 1
  • 0.55 within cluster 2
  • 0.51 within cluster 3
  • 0.77 within cluster 4
  • 0.66 within cluster 5
Characteristic taxa
##                          cluster indicator_value probability
## cistenides_granulata           1          0.2393       0.007
## crenella_decussata             1          0.1781       0.009
## mesodesma_arctatum             2          0.9709       0.001
## nephtys_caeca                  2          0.2328       0.009
## harpinia_propinqua             2          0.0802       0.031
## echinarachnius_parma           3          0.4747       0.001
## macoma_calcarea                4          0.5476       0.001
## bipalponephtys_neotena         4          0.3216       0.002
## pholoe_sp                      4          0.2173       0.015
## lamprops_fuscatus              4          0.1880       0.006
## diastylis_rathkei              4          0.1416       0.014
## retusa_obtusa                  4          0.1098       0.028
## holothuroidea                  4          0.1053       0.041
## leucon_leucon_nasicoides       5          0.6079       0.001
## protomedeia_grandimana         5          0.5819       0.001
## goniada_maculata               5          0.5556       0.001
## eudorellopsis_integra          5          0.5501       0.001
## ennucula_tenuis                5          0.4939       0.001
## maldanidae_spp                 5          0.4097       0.001
## nephtys_incisa                 5          0.3554       0.001
## quasimelita_formosa            5          0.3433       0.001
## thyasira_gouldi                5          0.3333       0.001
## polynoidae_spp                 5          0.2147       0.006
## chaetodermatida                5          0.1883       0.008
## sipuncula                      5          0.1707       0.009
## pontoporeia_femorata           5          0.1642       0.038
## oligochaeta                    5          0.1476       0.024
## eudorella_emarginata           5          0.1176       0.030
## 
## Sum of probabilities                 =  72.816 
## 
## Sum of Indicator Values              =  14.88 
## 
## Sum of Significant Indicator Values  =  9.04 
## 
## Number of Significant Indicators     =  28 
## 
## Significant Indicator Distribution
## 
##  1  2  3  4  5 
##  2  3  1  7 15
Phylum abundances by cluster
phylum cl1 cl2 cl3 cl4 cl5
Arthropoda 1296 23 135 517 1226
Mollusca 663 190 135 421 484
Annelida 598 19 135 815 684
Echinodermata 562 119 135 28 3
Nematoda 145 1 0 0 19
Nemertea 13 0 0 0 4
Cnidaria 6 0 0 0 0
Sipuncula 4 0 0 2 21
Brachiopoda 2 0 0 0 0
Platyhelminthes 1 0 0 2 0

SIMPER results between clusters 1 and 2 (mean between-group Bray-Curtis dissimilarity: 0.932)
  average sd ratio ava avb cumsum
mesodesma_arctatum 0.205 0.113 1.81 0.073 2.44 0.22
echinarachnius_parma 0.0973 0.0922 1.06 0.501 1.31 0.324
cistenides_granulata 0.0397 0.0704 0.565 0.52 0 0.367
nephtys_caeca 0.0364 0.0419 0.869 0.18 0.38 0.406
phoxocephalus_holbolli 0.0306 0.0572 0.535 0.333 0.162 0.439
strongylocentrotus_sp 0.0251 0.0516 0.486 0.263 0.116 0.466
macoma_calcarea 0.0237 0.0501 0.474 0.251 0.162 0.491
nematoda 0.0207 0.0541 0.382 0.249 0.0578 0.513
ameritella_agilis 0.0144 0.0404 0.355 0.157 0.0578 0.529
crenella_decussata 0.0143 0.0348 0.411 0.238 0 0.544
protomedeia_grandimana 0.0142 0.0473 0.301 0.24 0 0.559
orchomenella_minuta 0.0141 0.035 0.403 0.0611 0.149 0.574
limecola_balthica 0.0135 0.0393 0.343 0.174 0 0.589
pholoe_sp 0.0111 0.025 0.445 0.0516 0.116 0.601
harpinia_propinqua 0.011 0.0359 0.307 0.00815 0.207 0.613
polynoidae_spp 0.0105 0.0273 0.385 0.107 0.0578 0.624
amphipholis_squamata 0.00981 0.0403 0.243 0.122 0 0.634
scoloplos_armiger 0.0094 0.0383 0.245 0.139 0 0.644
caprella_septentrionalis 0.00939 0.0366 0.256 0.212 0 0.655
nephtys_incisa 0.0084 0.0221 0.38 0.0619 0.0578 0.664
nephtys_ciliata 0.00826 0.0289 0.286 0 0.116 0.672
harmothoe_imbricata 0.00797 0.0306 0.261 0.0795 0 0.681
phyllodoce_mucosa 0.00781 0.0247 0.317 0.0455 0.0578 0.689
ophiura_robusta 0.00775 0.0321 0.241 0.185 0 0.698
SIMPER results between clusters 1 and 3 (mean between-group Bray-Curtis dissimilarity: 0.91)
  average sd ratio ava avb cumsum
echinarachnius_parma 0.185 0.148 1.25 0.501 1.85 0.203
cistenides_granulata 0.0532 0.0876 0.607 0.52 0.0495 0.261
strongylocentrotus_sp 0.0363 0.07 0.519 0.263 0.157 0.301
phoxocephalus_holbolli 0.0276 0.0608 0.455 0.333 0 0.332
limecola_balthica 0.0224 0.0533 0.42 0.174 0.0495 0.356
scoloplos_armiger 0.0206 0.0586 0.351 0.139 0.0785 0.379
amphipholis_squamata 0.0205 0.0576 0.356 0.122 0.099 0.401
nephtys_caeca 0.0194 0.0441 0.44 0.18 0 0.423
nematoda 0.0192 0.0635 0.302 0.249 0 0.444
harmothoe_imbricata 0.0179 0.0494 0.362 0.0795 0.0785 0.463
protomedeia_grandimana 0.0172 0.0553 0.31 0.24 0 0.482
crenella_decussata 0.0171 0.0411 0.416 0.238 0 0.501
macoma_calcarea 0.0166 0.0419 0.395 0.251 0 0.519
ciliatocardium_ciliatum 0.0162 0.0518 0.313 0.0551 0.115 0.537
ameritella_agilis 0.014 0.0495 0.283 0.157 0 0.552
mya_arenaria 0.0137 0.0326 0.419 0.101 0.0495 0.567
psammonyx_nobilis 0.0124 0.0455 0.272 0.0637 0.0495 0.581
diastylis_sculpta 0.0119 0.0397 0.3 0.0852 0.0495 0.594
orchomenella_minuta 0.0119 0.0424 0.28 0.0611 0.0495 0.607
nephtys_bucera 0.0115 0.0292 0.394 0.0163 0.099 0.62
ophelia_limacina 0.0114 0.0309 0.368 0.0748 0.0495 0.632
caprella_septentrionalis 0.0107 0.0413 0.26 0.212 0 0.644
arrhoges_occidentalis 0.00918 0.0347 0.265 0.0211 0.0495 0.654
hiatella_arctica 0.00918 0.033 0.278 0.127 0 0.664
mesodesma_arctatum 0.00888 0.0446 0.199 0.073 0 0.674
ophiura_robusta 0.00878 0.0359 0.244 0.185 0 0.684
mytilus_sp 0.00724 0.0333 0.217 0.102 0 0.692
glycera_dibranchiata 0.00711 0.0353 0.201 0.0408 0 0.699
SIMPER results between clusters 1 and 4 (mean between-group Bray-Curtis dissimilarity: 0.947)
  average sd ratio ava avb cumsum
macoma_calcarea 0.0964 0.0717 1.34 0.251 1.62 0.102
bipalponephtys_neotena 0.0543 0.0666 0.814 0.0434 1.09 0.159
eudorellopsis_integra 0.0468 0.0636 0.736 0.0422 0.835 0.208
echinarachnius_parma 0.0331 0.0481 0.687 0.501 0.239 0.243
cistenides_granulata 0.0309 0.0514 0.602 0.52 0.0578 0.276
pholoe_sp 0.0304 0.0421 0.723 0.0516 0.576 0.308
pontoporeia_femorata 0.0279 0.0554 0.504 0.075 0.56 0.338
ennucula_tenuis 0.0261 0.0393 0.663 0.0748 0.38 0.365
phoxocephalus_holbolli 0.0218 0.0384 0.567 0.333 0.181 0.388
nephtys_caeca 0.0186 0.0328 0.568 0.18 0.16 0.408
axinopsida_orbiculata 0.0185 0.0398 0.463 0.0326 0.335 0.427
thracia_septentrionalis 0.0179 0.0433 0.415 0.127 0.235 0.446
protomedeia_grandimana 0.0148 0.0389 0.381 0.24 0.0971 0.462
diastylis_sculpta 0.0146 0.0338 0.431 0.0852 0.207 0.477
strongylocentrotus_sp 0.0143 0.0384 0.373 0.263 0 0.492
lamprops_fuscatus 0.0129 0.0241 0.536 0.0469 0.233 0.506
polynoidae_spp 0.0126 0.0284 0.445 0.107 0.191 0.519
diastylis_rathkei 0.0124 0.0328 0.377 0 0.237 0.532
nematoda 0.0123 0.0412 0.297 0.249 0 0.545
praxillella_praetermissa 0.0117 0.0438 0.268 0.0163 0.158 0.558
scoloplos_armiger 0.0117 0.0362 0.324 0.139 0.0713 0.57
crenella_decussata 0.0112 0.0278 0.404 0.238 0 0.582
goniada_maculata 0.0109 0.027 0.405 0.0422 0.181 0.593
hediste_diversicolor 0.0109 0.0227 0.483 0.0292 0.225 0.605
ameritella_agilis 0.0105 0.0325 0.323 0.157 0.0289 0.616
limecola_balthica 0.00998 0.0286 0.348 0.174 0 0.627
scoletoma_fragilis 0.00924 0.0252 0.367 0.0508 0.16 0.636
thyasira_sp 0.00911 0.0354 0.257 0.0271 0.11 0.646
sabellidae_spp 0.0091 0.0323 0.281 0.063 0.199 0.656
thyasira_gouldi 0.00839 0.0238 0.353 0.0374 0.115 0.664
glycera_sp 0.00824 0.0284 0.29 0.0408 0.0912 0.673
nephtys_incisa 0.00805 0.0194 0.414 0.0619 0.0836 0.682
caprella_septentrionalis 0.0078 0.031 0.252 0.212 0 0.69
oligochaeta 0.0074 0.026 0.285 0.0129 0.182 0.698
SIMPER results between clusters 1 and 5 (mean between-group Bray-Curtis dissimilarity: 0.951)
  average sd ratio ava avb cumsum
eudorellopsis_integra 0.0732 0.0569 1.29 0.0422 1.65 0.077
protomedeia_grandimana 0.0618 0.0473 1.31 0.24 1.36 0.142
ennucula_tenuis 0.0471 0.0433 1.09 0.0748 1.06 0.192
leucon_leucon_nasicoides 0.0404 0.0437 0.925 0 0.898 0.234
maldanidae_spp 0.0391 0.0542 0.722 0.0597 0.879 0.275
goniada_maculata 0.039 0.0318 1.23 0.0422 0.823 0.316
macoma_calcarea 0.0365 0.0328 1.12 0.251 0.77 0.355
thyasira_gouldi 0.0288 0.039 0.739 0.0374 0.648 0.385
pontoporeia_femorata 0.0283 0.0452 0.626 0.075 0.552 0.415
bipalponephtys_neotena 0.0281 0.0314 0.894 0.0434 0.653 0.444
cistenides_granulata 0.0255 0.0366 0.697 0.52 0.165 0.471
quasimelita_formosa 0.0252 0.0368 0.686 0.0292 0.565 0.497
nephtys_incisa 0.0242 0.0285 0.847 0.0619 0.536 0.523
polynoidae_spp 0.0213 0.0281 0.757 0.107 0.431 0.545
echinarachnius_parma 0.0209 0.0349 0.598 0.501 0 0.567
nematoda 0.0152 0.0345 0.44 0.249 0.16 0.583
phoxocephalus_holbolli 0.0145 0.03 0.483 0.333 0.0136 0.598
oligochaeta 0.0142 0.0318 0.447 0.0129 0.328 0.613
pholoe_sp 0.0138 0.0196 0.705 0.0516 0.304 0.628
nephtys_caeca 0.0125 0.0284 0.441 0.18 0.0969 0.641
strongylocentrotus_sp 0.0116 0.0288 0.401 0.263 0.0136 0.653
axinopsida_orbiculata 0.0105 0.0281 0.374 0.0326 0.199 0.664
sipuncula 0.00964 0.0185 0.521 0.0292 0.221 0.674
crenella_decussata 0.00954 0.0223 0.428 0.238 0.0136 0.684
protomedeia_fasciata 0.00817 0.0246 0.333 0 0.171 0.693
SIMPER results between clusters 2 and 3 (mean between-group Bray-Curtis dissimilarity: 0.814)
  average sd ratio ava avb cumsum
mesodesma_arctatum 0.296 0.107 2.77 2.44 0 0.363
echinarachnius_parma 0.181 0.137 1.32 1.31 1.85 0.586
nephtys_caeca 0.0471 0.0497 0.946 0.38 0 0.643
strongylocentrotus_sp 0.0274 0.0503 0.544 0.116 0.157 0.677
orchomenella_minuta 0.0176 0.0346 0.508 0.149 0.0495 0.699
SIMPER results between clusters 2 and 4 (mean between-group Bray-Curtis dissimilarity: 0.954)
  average sd ratio ava avb cumsum
mesodesma_arctatum 0.163 0.0797 2.04 2.44 0 0.171
macoma_calcarea 0.105 0.0705 1.49 0.162 1.62 0.281
echinarachnius_parma 0.0765 0.0758 1.01 1.31 0.239 0.361
bipalponephtys_neotena 0.0576 0.0699 0.824 0 1.09 0.421
eudorellopsis_integra 0.0498 0.0672 0.742 0 0.835 0.474
pholoe_sp 0.0339 0.0419 0.808 0.116 0.576 0.509
nephtys_caeca 0.0283 0.0322 0.878 0.38 0.16 0.539
ennucula_tenuis 0.027 0.0413 0.653 0 0.38 0.567
pontoporeia_femorata 0.0265 0.0556 0.477 0 0.56 0.595
axinopsida_orbiculata 0.0191 0.0419 0.455 0 0.335 0.615
phoxocephalus_holbolli 0.0156 0.0328 0.474 0.162 0.181 0.631
thracia_septentrionalis 0.0155 0.0451 0.343 0 0.235 0.647
diastylis_rathkei 0.0133 0.0344 0.385 0 0.237 0.661
polynoidae_spp 0.0131 0.0287 0.457 0.0578 0.191 0.675
lamprops_fuscatus 0.0123 0.0245 0.502 0 0.233 0.688
diastylis_sculpta 0.0116 0.0295 0.392 0 0.207 0.7
SIMPER results between clusters 2 and 5 (mean between-group Bray-Curtis dissimilarity: 0.98)
  average sd ratio ava avb cumsum
mesodesma_arctatum 0.122 0.0499 2.45 2.44 0 0.125
eudorellopsis_integra 0.0792 0.0587 1.35 0 1.65 0.206
protomedeia_grandimana 0.0652 0.0478 1.36 0 1.36 0.272
echinarachnius_parma 0.0593 0.0603 0.982 1.31 0 0.333
ennucula_tenuis 0.0513 0.0457 1.12 0 1.06 0.385
leucon_leucon_nasicoides 0.0431 0.0454 0.95 0 0.898 0.429
maldanidae_spp 0.0411 0.0574 0.716 0 0.879 0.471
goniada_maculata 0.041 0.0329 1.24 0.0578 0.823 0.513
macoma_calcarea 0.0389 0.0344 1.13 0.162 0.77 0.553
thyasira_gouldi 0.0302 0.0413 0.732 0 0.648 0.583
bipalponephtys_neotena 0.0295 0.0327 0.903 0 0.653 0.614
pontoporeia_femorata 0.0284 0.0465 0.61 0 0.552 0.642
quasimelita_formosa 0.0266 0.0388 0.685 0 0.565 0.67
nephtys_incisa 0.0257 0.0298 0.862 0.0578 0.536 0.696
SIMPER results between clusters 3 and 4 (mean between-group Bray-Curtis dissimilarity: 0.968)
  average sd ratio ava avb cumsum
echinarachnius_parma 0.142 0.0978 1.45 1.85 0.239 0.147
macoma_calcarea 0.135 0.0825 1.64 0 1.62 0.286
bipalponephtys_neotena 0.0676 0.0805 0.84 0 1.09 0.356
eudorellopsis_integra 0.0596 0.0793 0.751 0 0.835 0.418
pholoe_sp 0.0371 0.0513 0.722 0 0.576 0.456
ennucula_tenuis 0.0336 0.0504 0.666 0 0.38 0.491
pontoporeia_femorata 0.0305 0.0636 0.48 0 0.56 0.522
axinopsida_orbiculata 0.0227 0.0495 0.459 0 0.335 0.546
thracia_septentrionalis 0.0189 0.0548 0.346 0 0.235 0.565
diastylis_sculpta 0.0163 0.0353 0.461 0.0495 0.207 0.582
nephtys_caeca 0.0157 0.0381 0.412 0 0.16 0.598
diastylis_rathkei 0.0157 0.0399 0.393 0 0.237 0.614
lamprops_fuscatus 0.0144 0.0284 0.507 0 0.233 0.629
praxillella_praetermissa 0.014 0.054 0.26 0 0.158 0.644
scoloplos_armiger 0.0132 0.0399 0.331 0.0785 0.0713 0.657
hediste_diversicolor 0.0126 0.0271 0.463 0 0.225 0.67
strongylocentrotus_sp 0.0124 0.0331 0.373 0.157 0 0.683
polynoidae_spp 0.0113 0.0308 0.369 0 0.191 0.695
SIMPER results between clusters 3 and 5 (mean between-group Bray-Curtis dissimilarity: 0.998)
  average sd ratio ava avb cumsum
echinarachnius_parma 0.109 0.0537 2.03 1.85 0 0.109
eudorellopsis_integra 0.0913 0.0665 1.37 0 1.65 0.201
protomedeia_grandimana 0.0751 0.0546 1.38 0 1.36 0.276
ennucula_tenuis 0.0591 0.0519 1.14 0 1.06 0.335
leucon_leucon_nasicoides 0.0499 0.0518 0.963 0 0.898 0.385
goniada_maculata 0.049 0.0378 1.3 0 0.823 0.434
maldanidae_spp 0.0474 0.0669 0.708 0 0.879 0.482
macoma_calcarea 0.0424 0.0382 1.11 0 0.77 0.524
thyasira_gouldi 0.0347 0.0468 0.74 0 0.648 0.559
bipalponephtys_neotena 0.0337 0.0368 0.915 0 0.653 0.593
pontoporeia_femorata 0.0331 0.0536 0.618 0 0.552 0.626
quasimelita_formosa 0.0306 0.0442 0.692 0 0.565 0.656
nephtys_incisa 0.0294 0.0345 0.851 0 0.536 0.686
SIMPER results between clusters 4 and 5 (mean between-group Bray-Curtis dissimilarity: 0.816)
  average sd ratio ava avb cumsum
eudorellopsis_integra 0.0584 0.0466 1.25 0.835 1.65 0.0717
protomedeia_grandimana 0.0523 0.0393 1.33 0.0971 1.36 0.136
macoma_calcarea 0.045 0.039 1.15 1.62 0.77 0.191
bipalponephtys_neotena 0.0431 0.0407 1.06 1.09 0.653 0.244
ennucula_tenuis 0.0391 0.0339 1.15 0.38 1.06 0.292
leucon_leucon_nasicoides 0.0353 0.0375 0.94 0.0289 0.898 0.335
pontoporeia_femorata 0.0342 0.0439 0.779 0.56 0.552 0.377
maldanidae_spp 0.0339 0.0465 0.73 0.0289 0.879 0.419
goniada_maculata 0.0329 0.027 1.22 0.181 0.823 0.459
thyasira_gouldi 0.0263 0.0337 0.778 0.115 0.648 0.491
pholoe_sp 0.0244 0.0258 0.945 0.576 0.304 0.521
quasimelita_formosa 0.0226 0.0315 0.717 0.0836 0.565 0.549
nephtys_incisa 0.0213 0.0247 0.864 0.0836 0.536 0.575
polynoidae_spp 0.02 0.0251 0.797 0.191 0.431 0.599
axinopsida_orbiculata 0.0183 0.0316 0.579 0.335 0.199 0.622
oligochaeta 0.0163 0.0316 0.515 0.182 0.328 0.642
protomedeia_fasciata 0.0111 0.0234 0.475 0.16 0.171 0.655
hediste_diversicolor 0.011 0.0196 0.561 0.225 0.13 0.669
thracia_septentrionalis 0.0107 0.0269 0.399 0.235 0.0487 0.682
nephtys_caeca 0.0107 0.0247 0.432 0.16 0.0969 0.695

3. Univariate regressions

We used linear models for the all regressions on diversity indices. Outliers and correlated variables were removed from these analyses. Variables have been standardized by mean and standard-deviation (coefficients need to be back-transformed to be used in predictive models).

3.1. Best model selection

This step was not used here as each models are necessary.

3.2. Significative variables selection

We identified which variables were selected after an AIC procedure to predict the best the parameters. Results of the variable selection, according to AIC, are shown on the tables below:

  • for the 0.5 mm community:
Variable (or combination) S N H J
depth + - + +
om/silt + + -
gravel + + +
sand + + -
clay + + + -
Adjusted \(R^{2}\) 0.33 0.5 0.27 0.16
Variable (or combination) S N H J
arsenic - -
cadmium - -
chromium/iron/manganese + - -
mercury - -
lead/copper/zinc + +
Adjusted \(R^{2}\) 0.18 0.49 0.07 0.02
  • for the 1 mm community:
Variable (or combination) S N H J
depth + - + +
om/silt
gravel -
sand - - -
clay - - -
Adjusted \(R^{2}\) 0.25 0.03 0.34 0.1
Variable (or combination) S N H J
arsenic
cadmium - -
chromium/iron/manganese
mercury
lead/copper/zinc + +
Adjusted \(R^{2}\) 0.08 0 0.05 0

Details of the regressions, with diagnostics and cross-validation, are summarized below.

0.5 mm community
Richness/habitat
## FULL MODEL
## Adjusted R2 is: 0.33
Fitting linear model: S ~ depth + om + gravel + sand + clay
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.02378 0.06373 0.3732 0.7095
depth 0.2425 0.07287 3.328 0.001097 * *
om 0.2862 0.07987 3.584 0.0004548 * * *
gravel 0.2016 0.09011 2.237 0.0267 *
sand 0.2542 0.1164 2.183 0.03054 *
clay 0.7458 0.1126 6.623 5.636e-10 * * * 
## RMSE from cross-validation: 0.8090011
Variance Inflation Factors
  depth om gravel sand clay
VIF 1.14 1.25 1.05 1.84 1.79 

## REDUCED MODEL
## Adjusted R2 is: 0.33
Fitting linear model: S ~ depth + om + gravel + sand + clay
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.02378 0.06373 0.3732 0.7095
depth 0.2425 0.07287 3.328 0.001097 * *
om 0.2862 0.07987 3.584 0.0004548 * * *
gravel 0.2016 0.09011 2.237 0.0267 *
sand 0.2542 0.1164 2.183 0.03054 *
clay 0.7458 0.1126 6.623 5.636e-10 * * * 
## RMSE from cross-validation: 0.8090011
Variance Inflation Factors
  depth om gravel sand clay
VIF 1.14 1.25 1.05 1.84 1.79

Density/habitat
## FULL MODEL
## Adjusted R2 is: 0.5
Fitting linear model: N ~ depth + om + gravel + sand + clay
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.01472 0.05775 0.2548 0.7992
depth -0.09499 0.06604 -1.438 0.1524
om 0.5369 0.07238 7.418 7.649e-12 * * *
gravel 0.1221 0.08167 1.495 0.137
sand 0.5185 0.1055 4.914 2.27e-06 * * *
clay 0.8915 0.1021 8.736 3.96e-15 * * * 
## RMSE from cross-validation: 0.7850903
Variance Inflation Factors
  depth om gravel sand clay
VIF 1.14 1.25 1.05 1.84 1.79 

## REDUCED MODEL
## Adjusted R2 is: 0.5
Fitting linear model: N ~ depth + om + gravel + sand + clay
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.01472 0.05775 0.2548 0.7992
depth -0.09499 0.06604 -1.438 0.1524
om 0.5369 0.07238 7.418 7.649e-12 * * *
gravel 0.1221 0.08167 1.495 0.137
sand 0.5185 0.1055 4.914 2.27e-06 * * *
clay 0.8915 0.1021 8.736 3.96e-15 * * * 
## RMSE from cross-validation: 0.7850903
Variance Inflation Factors
  depth om gravel sand clay
VIF 1.14 1.25 1.05 1.84 1.79

Diversity/habitat
## FULL MODEL
## Adjusted R2 is: 0.26
Fitting linear model: H ~ depth + om + gravel + sand + clay
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.05663 0.06356 0.891 0.3743
depth 0.5219 0.07268 7.181 2.822e-11 * * *
om 0.01009 0.07966 0.1267 0.8993
gravel 0.156 0.08988 1.735 0.08467
sand -0.07361 0.1161 -0.6339 0.5271
clay 0.2279 0.1123 2.029 0.04422 * 
## RMSE from cross-validation: 0.8101494
Variance Inflation Factors
  depth om gravel sand clay
VIF 1.14 1.25 1.05 1.84 1.79 

## REDUCED MODEL
## Adjusted R2 is: 0.27
Fitting linear model: H ~ depth + gravel + clay
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.05587 0.06327 0.883 0.3786
depth 0.535 0.07073 7.565 3.221e-12 * * *
gravel 0.1584 0.08587 1.844 0.06707
clay 0.2884 0.06988 4.127 5.989e-05 * * * 
## RMSE from cross-validation: 0.8019987
Variance Inflation Factors
  depth gravel clay
VIF 1.11 1 1.12

Evenness/habitat
## FULL MODEL
## Adjusted R2 is: 0.15
Fitting linear model: J ~ depth + om + gravel + sand + clay
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.05235 0.06563 0.7977 0.4263
depth 0.3094 0.07505 4.122 6.142e-05 * * *
om -0.1443 0.08226 -1.754 0.08146
gravel -0.004248 0.09281 -0.04577 0.9636
sand -0.2053 0.1199 -1.712 0.08889
clay -0.2228 0.116 -1.921 0.05654 
## RMSE from cross-validation: 0.8333639
Variance Inflation Factors
  depth om gravel sand clay
VIF 1.14 1.25 1.05 1.84 1.79 

## REDUCED MODEL
## Adjusted R2 is: 0.16
Fitting linear model: J ~ depth + om + sand + clay
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.05272 0.06493 0.8119 0.4181
depth 0.3095 0.07478 4.138 5.741e-05 * * *
om -0.1432 0.07888 -1.816 0.07132
sand -0.2041 0.1168 -1.748 0.08245
clay -0.2218 0.1134 -1.956 0.05228 
## RMSE from cross-validation: 0.8267531
Variance Inflation Factors
  depth om sand clay
VIF 1.14 1.21 1.8 1.75

Richness/metals
## FULL MODEL
## Adjusted R2 is: 0.17
Fitting linear model: S ~ arsenic + cadmium + chromium + mercury + lead
  Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.06047 0.0758 -0.7978 0.4264
arsenic -0.4048 0.1342 -3.017 0.003051 * *
cadmium -0.6834 0.1672 -4.087 7.426e-05 * * *
chromium -0.01251 0.138 -0.09062 0.9279
mercury -0.4632 0.1701 -2.723 0.007325 * *
lead 1.038 0.2052 5.06 1.333e-06 * * * 
## RMSE from cross-validation: 0.8958299
Variance Inflation Factors
  arsenic cadmium chromium mercury lead
VIF 1.56 2.08 1.75 1.43 2.7 

## REDUCED MODEL
## Adjusted R2 is: 0.18
Fitting linear model: S ~ arsenic + cadmium + mercury + lead
  Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.05982 0.07518 -0.7956 0.4276
arsenic -0.4045 0.1337 -3.026 0.002957 * *
cadmium -0.6892 0.154 -4.474 1.6e-05 * * *
mercury -0.4584 0.161 -2.847 0.005086 * *
lead 1.031 0.19 5.427 2.524e-07 * * * 
## RMSE from cross-validation: 0.8902463
Variance Inflation Factors
  arsenic cadmium mercury lead
VIF 1.56 1.92 1.36 2.51

Density/metals
## FULL MODEL
## Adjusted R2 is: 0.49
Fitting linear model: N ~ arsenic + cadmium + chromium + mercury + lead
  Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.1098 0.05881 -1.867 0.06407
arsenic -0.5128 0.1041 -4.926 2.398e-06 * * *
cadmium -0.7432 0.1297 -5.729 6.212e-08 * * *
chromium 0.2695 0.1071 2.517 0.01301 *
mercury -0.7299 0.132 -5.529 1.588e-07 * * *
lead 1.43 0.1592 8.986 1.907e-15 * * * 
## RMSE from cross-validation: 0.7065136
Variance Inflation Factors
  arsenic cadmium chromium mercury lead
VIF 1.56 2.08 1.75 1.43 2.7 

## REDUCED MODEL
## Adjusted R2 is: 0.49
Fitting linear model: N ~ arsenic + cadmium + chromium + mercury + lead
  Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.1098 0.05881 -1.867 0.06407
arsenic -0.5128 0.1041 -4.926 2.398e-06 * * *
cadmium -0.7432 0.1297 -5.729 6.212e-08 * * *
chromium 0.2695 0.1071 2.517 0.01301 *
mercury -0.7299 0.132 -5.529 1.588e-07 * * *
lead 1.43 0.1592 8.986 1.907e-15 * * * 
## RMSE from cross-validation: 0.7065136
Variance Inflation Factors
  arsenic cadmium chromium mercury lead
VIF 1.56 2.08 1.75 1.43 2.7

Diversity/metals
## FULL MODEL
## Adjusted R2 is: 0.06
Fitting linear model: H ~ arsenic + cadmium + chromium + mercury + lead
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.03115 0.07881 0.3952 0.6933
arsenic -0.115 0.1395 -0.8244 0.4112
cadmium -0.2287 0.1738 -1.316 0.1905
chromium -0.2563 0.1435 -1.786 0.0764
mercury 0.02354 0.1769 0.1331 0.8943
lead 0.2542 0.2133 1.192 0.2355 
## RMSE from cross-validation: 0.9303706
Variance Inflation Factors
  arsenic cadmium chromium mercury lead
VIF 1.56 2.08 1.75 1.43 2.7 

## REDUCED MODEL
## Adjusted R2 is: 0.07
Fitting linear model: H ~ chromium
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.0391 0.077 0.5078 0.6124
chromium -0.2812 0.08139 -3.455 0.0007288 * * * 
## RMSE from cross-validation: 0.9157629
Variance Inflation Factors
  chromium
VIF 1

Evenness/metals
## FULL MODEL
## Adjusted R2 is: 0.03
Fitting linear model: J ~ arsenic + cadmium + chromium + mercury + lead
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.07716 0.07843 0.9838 0.3269
arsenic 0.1621 0.1388 1.167 0.2451
cadmium 0.2536 0.173 1.466 0.145
chromium -0.238 0.1428 -1.666 0.09799
mercury 0.1657 0.176 0.9411 0.3483
lead -0.3184 0.2123 -1.5 0.1359 
## RMSE from cross-validation: 0.9265784
Variance Inflation Factors
  arsenic cadmium chromium mercury lead
VIF 1.56 2.08 1.75 1.43 2.7 

## REDUCED MODEL
## Adjusted R2 is: 0.02
Fitting linear model: J ~ chromium
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.05581 0.07726 0.7224 0.4713
chromium -0.1744 0.08166 -2.136 0.03445 * 
## RMSE from cross-validation: 0.9269077
Variance Inflation Factors
  chromium
VIF 1

1 mm community
Richness/habitat
## FULL MODEL
## Adjusted R2 is: 0.25
Fitting linear model: S ~ depth + om + gravel + sand + clay
  Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.04634 0.06256 -0.7407 0.4598
depth 0.2715 0.06482 4.188 4.307e-05 * * *
om -0.04458 0.1117 -0.3991 0.6903
gravel -0.1185 0.08561 -1.384 0.1679
sand -0.4367 0.1322 -3.304 0.001141 * *
clay -0.5032 0.1403 -3.586 0.0004272 * * * 
## RMSE from cross-validation: 0.8934522
Variance Inflation Factors
  depth om gravel sand clay
VIF 1.06 1.81 1.03 2.1 1.45 

## REDUCED MODEL
## Adjusted R2 is: 0.25
Fitting linear model: S ~ depth + sand + clay
  Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.03361 0.06184 -0.5436 0.5874
depth 0.2678 0.06475 4.136 5.298e-05 * * *
sand -0.3869 0.07612 -5.083 8.825e-07 * * *
clay -0.4563 0.114 -4.001 9.001e-05 * * * 
## RMSE from cross-validation: 0.8673699
Variance Inflation Factors
  depth sand clay
VIF 1.06 1.21 1.18

Density/habitat
## FULL MODEL
## Adjusted R2 is: 0.02
Fitting linear model: N ~ depth + om + gravel + sand + clay
  Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.0211 0.07296 -0.2892 0.7727
depth -0.1713 0.07559 -2.266 0.02458 *
om -0.09757 0.1303 -0.749 0.4548
gravel 0.002914 0.09984 0.02919 0.9767
sand -0.29 0.1542 -1.881 0.06147
clay -0.3748 0.1636 -2.291 0.02309 * 
## RMSE from cross-validation: 1.008745
Variance Inflation Factors
  depth om gravel sand clay
VIF 1.06 1.81 1.03 2.1 1.45 

## REDUCED MODEL
## Adjusted R2 is: 0.03
Fitting linear model: N ~ depth + sand + clay
  Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.01888 0.07186 -0.2627 0.7931
depth -0.1719 0.07525 -2.285 0.02341 *
sand -0.1969 0.08846 -2.226 0.02718 *
clay -0.3066 0.1325 -2.314 0.02174 * 
## RMSE from cross-validation: 1.002598
Variance Inflation Factors
  depth sand clay
VIF 1.06 1.21 1.18

Diversity/habitat
## FULL MODEL
## Adjusted R2 is: 0.34
Fitting linear model: H ~ depth + om + gravel + sand + clay
  Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.02566 0.05866 -0.4374 0.6623
depth 0.4303 0.06078 7.079 2.765e-11 * * *
om 0.06608 0.1047 0.631 0.5288
gravel -0.1077 0.08027 -1.341 0.1815
sand -0.2444 0.124 -1.971 0.05013
clay -0.2757 0.1316 -2.096 0.03742 * 
## RMSE from cross-validation: 0.8438226
Variance Inflation Factors
  depth om gravel sand clay
VIF 1.06 1.81 1.03 2.1 1.45 

## REDUCED MODEL
## Adjusted R2 is: 0.34
Fitting linear model: H ~ depth + gravel + sand + clay
  Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.02847 0.0584 -0.4875 0.6265
depth 0.4311 0.06067 7.105 2.348e-11 * * *
gravel -0.119 0.0781 -1.524 0.1292
sand -0.3082 0.07143 -4.315 2.564e-05 * * *
clay -0.3236 0.1073 -3.017 0.002901 * * 
## RMSE from cross-validation: 0.8399062
Variance Inflation Factors
  depth gravel sand clay
VIF 1.06 1.01 1.21 1.18

Evenness/habitat
## FULL MODEL
## Adjusted R2 is: 0.08
Fitting linear model: J ~ depth + om + gravel + sand + clay
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.01566 0.06839 0.2289 0.8192
depth 0.2928 0.07086 4.133 5.383e-05 * * *
om 0.02954 0.1221 0.2419 0.8091
gravel 0.008159 0.09359 0.08718 0.9306
sand -0.04328 0.1445 -0.2995 0.7649
clay -0.02071 0.1534 -0.135 0.8927 
## RMSE from cross-validation: 0.9552492
Variance Inflation Factors
  depth om gravel sand clay
VIF 1.06 1.81 1.03 2.1 1.45 

## REDUCED MODEL
## Adjusted R2 is: 0.1
Fitting linear model: J ~ depth
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.01448 0.0664 0.2181 0.8276
depth 0.3126 0.06602 4.735 4.225e-06 * * * 
## RMSE from cross-validation: 0.9358617
Variance Inflation Factors
  depth
VIF 1

Richness/metals
## FULL MODEL
## Adjusted R2 is: 0.07
Fitting linear model: S ~ arsenic + cadmium + chromium + mercury + lead
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.06323 0.08253 0.7661 0.4451
arsenic -0.1466 0.1335 -1.098 0.2742
cadmium -0.5481 0.1606 -3.413 0.0008755 * * *
chromium 0.01217 0.1638 0.07431 0.9409
mercury -0.001392 0.1293 -0.01077 0.9914
lead 0.4503 0.2727 1.651 0.1013 
## RMSE from cross-validation: 0.9298714
Variance Inflation Factors
  arsenic cadmium chromium mercury lead
VIF 1.65 1.85 1.89 1.48 3.17 

## REDUCED MODEL
## Adjusted R2 is: 0.08
Fitting linear model: S ~ cadmium + lead
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.06172 0.08196 0.7531 0.4529
cadmium -0.5082 0.149 -3.409 0.000881 * * *
lead 0.3104 0.1476 2.103 0.03751 * 
## RMSE from cross-validation: 0.9219954
Variance Inflation Factors
  cadmium lead
VIF 1.73 1.73

Density/metals
## FULL MODEL
## Adjusted R2 is: -0.01
Fitting linear model: N ~ arsenic + cadmium + chromium + mercury + lead
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.01452 0.09066 0.1602 0.873
arsenic -0.1569 0.1467 -1.07 0.287
cadmium -0.161 0.1764 -0.9126 0.3633
chromium -0.2011 0.18 -1.117 0.2661
mercury -0.1079 0.142 -0.7597 0.4489
lead 0.4704 0.2995 1.57 0.1189 
## RMSE from cross-validation: 1.030112
Variance Inflation Factors
  arsenic cadmium chromium mercury lead
VIF 1.65 1.85 1.89 1.48 3.17 

## REDUCED MODEL
## Adjusted R2 is: 0
Fitting linear model: N ~ 1
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.01849 0.08981 0.2058 0.8373 
## RMSE from cross-validation: 1.011527

Quitting from lines 729-731 (C1_analyses_B.Rmd) Error in Qr$qr[p1, p1, drop = FALSE] : indice hors limites De plus : There were 35 warnings (use warnings() to see them)

Diversity/metals
## FULL MODEL
## Adjusted R2 is: 0.04
Fitting linear model: H ~ arsenic + cadmium + chromium + mercury + lead
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.09394 0.08016 1.172 0.2435
arsenic -0.1326 0.1297 -1.023 0.3086
cadmium -0.4559 0.156 -2.923 0.004141 * *
chromium 0.006562 0.1591 0.04124 0.9672
mercury 0.03018 0.1255 0.2404 0.8104
lead 0.3954 0.2648 1.493 0.1381 
## RMSE from cross-validation: 0.8995954
Variance Inflation Factors
  arsenic cadmium chromium mercury lead
VIF 1.65 1.85 1.89 1.48 3.17 

## REDUCED MODEL
## Adjusted R2 is: 0.05
Fitting linear model: H ~ cadmium + lead
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.09219 0.07962 1.158 0.2492
cadmium -0.4268 0.1448 -2.948 0.003831 * *
lead 0.2923 0.1434 2.038 0.04365 * 
## RMSE from cross-validation: 0.8942355
Variance Inflation Factors
  cadmium lead
VIF 1.73 1.73

Evenness/metals
## FULL MODEL
## Adjusted R2 is: -0.04
Fitting linear model: J ~ arsenic + cadmium + chromium + mercury + lead
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.06202 0.07961 0.779 0.4375
arsenic -0.05693 0.1288 -0.4421 0.6592
cadmium -0.04309 0.1549 -0.2782 0.7813
chromium 0.05701 0.158 0.3607 0.7189
mercury 0.03799 0.1247 0.3047 0.7611
lead -0.004916 0.263 -0.01869 0.9851 
## RMSE from cross-validation: 0.8928066
Variance Inflation Factors
  arsenic cadmium chromium mercury lead
VIF 1.65 1.85 1.89 1.48 3.17 

## REDUCED MODEL
## Adjusted R2 is: 0
Fitting linear model: J ~ 1
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.06244 0.07799 0.8006 0.4249 
## RMSE from cross-validation: 0.873627

Quitting from lines 753-755 (C1_analyses_B.Rmd) Error in Qr\(qr[p1, p1, drop = FALSE] : indice hors limites De plus : Warning messages: 1: In CVlm(data = lm_out\)model, form.lm = lm_out, m = 5, printit = F) :

As there is >1 explanatory variable, cross-validation predicted values for a fold are not a linear function of corresponding overall predicted values. Lines that are shown for the different folds are approximate

2: In CVlm(data = lm_out$model, form.lm = lm_out, m = 5, printit = F) :

As there is >1 explanatory variable, cross-validation predicted values for a fold are not a linear function of corresponding overall predicted values. Lines that are shown for the different folds are approximate

3: In CVlm(data = lm_out$model, form.lm = lm_out, m = 5, printit = F) :

As there is >1 explanatory variable, cross-validation predicted values for a fold are not a linear function of corresponding overall predicted values. Lines that are shown for the different folds are approximate

4: In CVlm(data = lm_out$model, form.lm = lm_out, m = 5, printit = F) :

As there is >1 explanatory variable, cross-validation predicted values for a fold are not a linear function of corresponding overall predicted values. Lines that are shown for the different folds are approximate

4. Multivariate regression

Independant variables are habitat parameters or heavy metal concentrations, dependant variables are species abundances for each community. Variables have been standardized by mean and standard-deviation, and outliers and correlated variables have been excluded.

This analysis has been done on PRIMER, with a DistLM to identify the variables that explain the most the community variability and with a dbRDA to plot the results.

0.5 mm community
Habitat

Variables selected by the DistLM procedure have a \(R^{2}\) of 0.27.

Metals

Variables selected by the DistLM procedure have a \(R^{2}\) of 0.18.

1 mm community
Habitat

Variables selected by the DistLM procedure have a \(R^{2}\) of 0.14.

Metals

Variables selected by the DistLM procedure have a \(R^{2}\) of 0.07.

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